Artificial Intelligence

There’s no doubt that artificial intelligence (AI) and its underlying technology building blocks are top of mind for enterprises today. But who’s driving this change and its adoption within their organizations? On the surface, it may appear that AI is …

The promise of artificial intelligence (AI) has permeated across the enterprise giving hopes of amping up automation, enriching insights, streamlining processes, augmenting workers, and in many ways making our lives as consumers, employees, and custome…

Building AI applications is hard work, but cloud vendors are making it easy by exposing simple-to-call, pay-as-you-use APIs. Want to add real-time speech recognition to your app? There’s an API for that. Want to recognize faces in an image? There…

Your customers are very literally telling you what they want, what they think about your products and services, and what they think about their experiences with your company. They are doing this, often unwittingly, through conversations with your salespeople, your customer service reps, with each other online, and increasingly with virtual agents. Up until now, […]

This week, Google announced the acquisition of key HTC assets. This will give them some of the hardware technology expertise, the design skills and the experience in smartphone retail distribution they badly need. Due to Android’s massive fragmentation, Google needs to control the distribution of its services, to reduce its traffic acquisition costs and to […]

It is the best of times, and the worst of times to be a data scientist (apologies to Charles Dickens). It is the best of times, because, like never before, we have access to data, computing power, and rapidly evolving tools to create insights and applications with the potential to revolutionize business and the world […]

That is exactly what Forrester wants to find out – is there something behind the AI and Cognitive Computing hype? What my research directors ask, “Is there a there there?”

AI and Cognitive Computing have captured the imagination and interest of organization large and small but does anyone really know how to bring this new capability in and get value from it? Will AI and Cognitive really change businesses and consumer experiences? And the bigger question – WHEN will this happen?

It is time to roll-up the sleeves and look beyond conversations, vendor pitches and media coverage to really define what AI and Cognitive Computing mean for businesses, are businesses ready, where they will invest, and who they will turn to to build these innovated solutions, and what benefits will result. As such, Forrester launched its Global Artificial Intelligence Survey and is reaching out to you – executives, data scientists, data analysts, developers, architects and researchers – to put a finger on the pulse. We would appreciate you take a little time out of your day to tell us your point of view.

As a thank you, you will receive a complimentary summary report of the findings.

If you have a great story to share that provides a perspective on what AI and Cogntivive can do, what benefits is has provided your company, and can share you learnings and best practices, we are also recruiting for interviews.

You can’t turn anywhere without bumping into artificial intelligence, machine learning, or cognitive computing jumping out at you. Our cars brake for us, park for us, and some are even driving us. Our movie lists are filled with Ex Machina, Her, and Lucy. The news tells about the latest vendor and cool use of technology, minute by minute. Vendors are filling our voicemail and email with enticements. It’s all so very cool!

But cool doesn’t build a business. Results do.

Which brings me to the biggest barrier companies have in adopting artificial intelligence. Companies are asking the wrong questions:

These questions put artificial intelligence into the traditional analytic processes and technology adoption box. These questions assume you will begin from the same starting point as you did for big data. You are wrong: Artificial intelligence starts with the problem to solve and works backward.

To succeed at artificial intelligence you need to ask the right questions:

You can’t turn anywhere without bumping into artificial intelligence, machine learning, or cognitive computing jumping out at you. Our cars brake for us, park for us, and some are even driving us. Our movie lists are filled with Ex Machina, Her, and Lucy. The news tells about the latest vendor and cool use of technology, minute by minute. Vendors are filling our voicemail and email with enticements. It’s all so very cool!

But cool doesn’t build a business. Results do.

Which brings me to the biggest barrier companies have in adopting artificial intelligence. Companies are asking the wrong questions:

These questions put artificial intelligence into the traditional analytic processes and technology adoption box. These questions assume you will begin from the same starting point as you did for big data. You are wrong: Artificial intelligence starts with the problem to solve and works backward.

To succeed at artificial intelligence you need to ask the right questions:

You can’t bring up semantics without someone inserting an apology for the geekiness of the discussion. If you’re a data person like me, geek away! But for everyone else, it’s a topic best left alone. Well, like every geek, the semantic geeks now have their day — and may just rule the data world.

It begins with a seemingly innocent set of questions:

“Is there a better way to master my data?”

“Is there a better way to understand the data I have?”

“Is there a better way to bring data and content together?”

“Is there a better way to personalize data and insight to be relevant?”

Semantics discussions today are born out of the data chaos that our traditional data management and governance capabilities are struggling under. They’re born out of the fact that even with the best big data technology and analytics being adopted, business stakeholder satisfaction with analytics has decreased by 21% from 2014 to 2015, according to Forrester’s Global Business Technographics® Data And Analytics Survey, 2015. Innovative data architects and vendors realize that semantics is the key to bringing context and meaning to our information so we can extract those much-needed business insights, at scale, and more importantly, personalized.

You can’t bring up semantics without someone inserting an apology for the geekiness of the discussion. If you’re a data person like me, geek away! But for everyone else, it’s a topic best left alone. Well, like every geek, the semantic geeks now have their day — and may just rule the data world.

It begins with a seemingly innocent set of questions:

“Is there a better way to master my data?”

“Is there a better way to understand the data I have?”

“Is there a better way to bring data and content together?”

“Is there a better way to personalize data and insight to be relevant?”

Semantics discussions today are born out of the data chaos that our traditional data management and governance capabilities are struggling under. They’re born out of the fact that even with the best big data technology and analytics being adopted, business stakeholder satisfaction with analytics has decreased by 21% from 2014 to 2015, according to Forrester’s Global Business Technographics® Data And Analytics Survey, 2015. Innovative data architects and vendors realize that semantics is the key to bringing context and meaning to our information so we can extract those much-needed business insights, at scale, and more importantly, personalized.